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<div class="title">tree/cuda/reduce_inline.h</div>  </div>
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<div class="fragment"><pre class="fragment"><a name="l00001"></a>00001 <span class="comment">/*</span>
<a name="l00002"></a>00002 <span class="comment"> * Copyright (c) 2010-2011, NVIDIA Corporation</span>
<a name="l00003"></a>00003 <span class="comment"> * All rights reserved.</span>
<a name="l00004"></a>00004 <span class="comment"> *</span>
<a name="l00005"></a>00005 <span class="comment"> * Redistribution and use in source and binary forms, with or without</span>
<a name="l00006"></a>00006 <span class="comment"> * modification, are permitted provided that the following conditions are met:</span>
<a name="l00007"></a>00007 <span class="comment"> *   * Redistributions of source code must retain the above copyright</span>
<a name="l00008"></a>00008 <span class="comment"> *     notice, this list of conditions and the following disclaimer.</span>
<a name="l00009"></a>00009 <span class="comment"> *   * Redistributions in binary form must reproduce the above copyright</span>
<a name="l00010"></a>00010 <span class="comment"> *     notice, this list of conditions and the following disclaimer in the</span>
<a name="l00011"></a>00011 <span class="comment"> *     documentation and/or other materials provided with the distribution.</span>
<a name="l00012"></a>00012 <span class="comment"> *   * Neither the name of NVIDIA Corporation nor the</span>
<a name="l00013"></a>00013 <span class="comment"> *     names of its contributors may be used to endorse or promote products</span>
<a name="l00014"></a>00014 <span class="comment"> *     derived from this software without specific prior written permission.</span>
<a name="l00015"></a>00015 <span class="comment"> *</span>
<a name="l00016"></a>00016 <span class="comment"> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS &quot;AS IS&quot; AND</span>
<a name="l00017"></a>00017 <span class="comment"> * ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED</span>
<a name="l00018"></a>00018 <span class="comment"> * WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE</span>
<a name="l00019"></a>00019 <span class="comment"> * DISCLAIMED. IN NO EVENT SHALL &lt;COPYRIGHT HOLDER&gt; BE LIABLE FOR ANY</span>
<a name="l00020"></a>00020 <span class="comment"> * DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES</span>
<a name="l00021"></a>00021 <span class="comment"> * (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;</span>
<a name="l00022"></a>00022 <span class="comment"> * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND</span>
<a name="l00023"></a>00023 <span class="comment"> * ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT</span>
<a name="l00024"></a>00024 <span class="comment"> * (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS</span>
<a name="l00025"></a>00025 <span class="comment"> * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.</span>
<a name="l00026"></a>00026 <span class="comment"> */</span>
<a name="l00027"></a>00027 
<a name="l00028"></a>00028 <span class="preprocessor">#pragma once</span>
<a name="l00029"></a>00029 <span class="preprocessor"></span>
<a name="l00030"></a>00030 <span class="preprocessor">#include &lt;nih/basic/types.h&gt;</span>
<a name="l00031"></a>00031 <span class="preprocessor">#include &lt;thrust/detail/backend/dereference.h&gt;</span>
<a name="l00032"></a>00032 
<a name="l00033"></a>00033 <span class="keyword">namespace </span>nih {
<a name="l00034"></a>00034 <span class="keyword">namespace </span>cuda {
<a name="l00035"></a>00035 
<a name="l00036"></a>00036 <span class="keyword">namespace </span>treereduce {
<a name="l00037"></a>00037 
<a name="l00038"></a>00038 <span class="comment">// reduce leaf values</span>
<a name="l00039"></a>00039 <span class="keyword">template</span> &lt;u<span class="keywordtype">int</span>32 BLOCK_SIZE, <span class="keyword">typename</span> Tree, <span class="keyword">typename</span> Input_iterator, <span class="keyword">typename</span> Output_iterator, <span class="keyword">typename</span> Operator&gt;
<a name="l00040"></a>00040 __global__ <span class="keywordtype">void</span> reduce_leaves_kernel(
<a name="l00041"></a>00041     <span class="keyword">const</span> Tree              tree,
<a name="l00042"></a>00042     <span class="keyword">const</span> uint32            n_leaves,
<a name="l00043"></a>00043     <span class="keyword">const</span> Input_iterator    in_values,
<a name="l00044"></a>00044     Output_iterator         out_values,
<a name="l00045"></a>00045     <span class="keyword">const</span> Operator          op,
<a name="l00046"></a>00046     <span class="keyword">const</span> <span class="keyword">typename</span> std::iterator_traits&lt;Output_iterator&gt;::value_type def_value)
<a name="l00047"></a>00047 {
<a name="l00048"></a>00048     <span class="keyword">const</span> uint32 grid_size = gridDim.x * blockDim.x;
<a name="l00049"></a>00049 
<a name="l00050"></a>00050     <span class="comment">// loop through all logical blocks associated to this physical one</span>
<a name="l00051"></a>00051     <span class="keywordflow">for</span> (uint32 base_idx = blockIdx.x * BLOCK_SIZE;
<a name="l00052"></a>00052         base_idx &lt; n_leaves;
<a name="l00053"></a>00053         base_idx += grid_size)
<a name="l00054"></a>00054     {
<a name="l00055"></a>00055         <span class="keyword">const</span> uint32 leaf_id = threadIdx.x + base_idx;
<a name="l00056"></a>00056 
<a name="l00057"></a>00057         <span class="keywordflow">if</span> (leaf_id &lt; n_leaves)
<a name="l00058"></a>00058         {
<a name="l00059"></a>00059             <span class="keyword">const</span> uint2 leaf = tree.get_leaf( leaf_id );
<a name="l00060"></a>00060             <span class="keyword">const</span> uint32 begin = leaf.x;
<a name="l00061"></a>00061             <span class="keyword">const</span> uint32 end   = leaf.y;
<a name="l00062"></a>00062 
<a name="l00063"></a>00063             <span class="keyword">typename</span> std::iterator_traits&lt;Output_iterator&gt;::value_type value = def_value;
<a name="l00064"></a>00064             <span class="keywordflow">for</span> (uint32 i = begin; i &lt; end; ++i)
<a name="l00065"></a>00065                 value = op( value, thrust::detail::backend::dereference( in_values + i ) );
<a name="l00066"></a>00066 
<a name="l00067"></a>00067             thrust::detail::backend::dereference( out_values, leaf_id ) = value;
<a name="l00068"></a>00068         }
<a name="l00069"></a>00069     }
<a name="l00070"></a>00070 }
<a name="l00071"></a>00071 
<a name="l00072"></a>00072 <span class="comment">// reduce leaf values</span>
<a name="l00073"></a>00073 <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Tree, <span class="keyword">typename</span> Input_iterator, <span class="keyword">typename</span> Output_iterator, <span class="keyword">typename</span> Operator&gt;
<a name="l00074"></a>00074 <span class="keywordtype">void</span> reduce_leaves(
<a name="l00075"></a>00075     <span class="keyword">const</span> Tree              tree,
<a name="l00076"></a>00076     <span class="keyword">const</span> Input_iterator    in_values,
<a name="l00077"></a>00077     Output_iterator         out_values,
<a name="l00078"></a>00078     <span class="keyword">const</span> Operator          op,
<a name="l00079"></a>00079     <span class="keyword">const</span> <span class="keyword">typename</span> std::iterator_traits&lt;Output_iterator&gt;::value_type def_value)
<a name="l00080"></a>00080 {
<a name="l00081"></a>00081     <span class="keyword">const</span> uint32 n_leaves = tree.get_leaf_count();
<a name="l00082"></a>00082 
<a name="l00083"></a>00083     <span class="keyword">const</span> uint32 BLOCK_SIZE = 128;
<a name="l00084"></a>00084     <span class="keyword">const</span> <span class="keywordtype">size_t</span> max_blocks = thrust::detail::backend::cuda::arch::max_active_blocks(reduce_leaves_kernel&lt;BLOCK_SIZE, Tree, Input_iterator, Output_iterator, Operator&gt;, BLOCK_SIZE, 0);
<a name="l00085"></a>00085     <span class="keyword">const</span> <span class="keywordtype">size_t</span> n_blocks   = <a class="code" href="group__vectors.html#ga5809911d15c32de18955c59865379695">nih::min</a>( max_blocks, (n_leaves + BLOCK_SIZE-1) / BLOCK_SIZE );
<a name="l00086"></a>00086 
<a name="l00087"></a>00087     reduce_leaves_kernel&lt;BLOCK_SIZE&gt; &lt;&lt;&lt;n_blocks,BLOCK_SIZE&gt;&gt;&gt; (
<a name="l00088"></a>00088         tree,
<a name="l00089"></a>00089         n_leaves,
<a name="l00090"></a>00090         in_values,
<a name="l00091"></a>00091         out_values,
<a name="l00092"></a>00092         op,
<a name="l00093"></a>00093         def_value );
<a name="l00094"></a>00094 
<a name="l00095"></a>00095     cudaThreadSynchronize();
<a name="l00096"></a>00096 }
<a name="l00097"></a>00097 
<a name="l00098"></a>00098 <span class="comment">// reduce a level</span>
<a name="l00099"></a>00099 <span class="keyword">template</span> &lt;u<span class="keywordtype">int</span>32 BLOCK_SIZE, <span class="keyword">typename</span> Tree, <span class="keyword">typename</span> Leaf_iterator, <span class="keyword">typename</span> Output_iterator, <span class="keyword">typename</span> Operator&gt;
<a name="l00100"></a>00100 __global__ <span class="keywordtype">void</span> reduce_level_kernel(
<a name="l00101"></a>00101     <span class="keyword">const</span> Tree              tree,
<a name="l00102"></a>00102     <span class="keyword">const</span> uint32            begin,
<a name="l00103"></a>00103     <span class="keyword">const</span> uint32            end,
<a name="l00104"></a>00104     Leaf_iterator           leaf_values,
<a name="l00105"></a>00105     Output_iterator         out_values,
<a name="l00106"></a>00106     <span class="keyword">const</span> Operator          op)
<a name="l00107"></a>00107 {
<a name="l00108"></a>00108     <span class="keyword">const</span> uint32 grid_size = gridDim.x * blockDim.x;
<a name="l00109"></a>00109 
<a name="l00110"></a>00110     <span class="comment">// loop through all logical blocks associated to this physical one</span>
<a name="l00111"></a>00111     <span class="keywordflow">for</span> (uint32 base_idx = blockIdx.x * BLOCK_SIZE + begin;
<a name="l00112"></a>00112         base_idx &lt; end;
<a name="l00113"></a>00113         base_idx += grid_size)
<a name="l00114"></a>00114     {
<a name="l00115"></a>00115         <span class="keyword">const</span> uint32 node_id = threadIdx.x + base_idx;
<a name="l00116"></a>00116 
<a name="l00117"></a>00117         <span class="keywordflow">if</span> (node_id &lt; end)
<a name="l00118"></a>00118         {
<a name="l00119"></a>00119             <span class="keyword">const</span> <span class="keyword">typename</span> Tree::node_type node = tree.get_node( node_id );
<a name="l00120"></a>00120 
<a name="l00121"></a>00121             <span class="keywordflow">if</span> (node.is_leaf())
<a name="l00122"></a>00122             {
<a name="l00123"></a>00123                 <span class="comment">// copy the corresponding leaf value</span>
<a name="l00124"></a>00124                 <span class="keyword">const</span> uint32 leaf_index = node.get_leaf_index();
<a name="l00125"></a>00125                 thrust::detail::backend::dereference( out_values + node_id ) = thrust::detail::backend::dereference( leaf_values + leaf_index );
<a name="l00126"></a>00126             }
<a name="l00127"></a>00127             <span class="keywordflow">else</span>
<a name="l00128"></a>00128             {
<a name="l00129"></a>00129                 <span class="comment">// reduce all child values</span>
<a name="l00130"></a>00130                 <span class="keyword">const</span> uint32 n_children = node.get_child_count();
<a name="l00131"></a>00131 
<a name="l00132"></a>00132                 <span class="keyword">typename</span> std::iterator_traits&lt;Output_iterator&gt;::value_type value =
<a name="l00133"></a>00133                     thrust::detail::backend::dereference( out_values, node.get_child(0) );
<a name="l00134"></a>00134                 <span class="keywordflow">for</span> (uint32 i = 1; i &lt; n_children; ++i)
<a name="l00135"></a>00135                     value = op( value, thrust::detail::backend::dereference( out_values, node.get_child(i) ) );
<a name="l00136"></a>00136 
<a name="l00137"></a>00137                 thrust::detail::backend::dereference( out_values, node_id ) = value;
<a name="l00138"></a>00138             }
<a name="l00139"></a>00139         }
<a name="l00140"></a>00140     }
<a name="l00141"></a>00141 }
<a name="l00142"></a>00142 
<a name="l00143"></a>00143 <span class="comment">// reduce leaf values</span>
<a name="l00144"></a>00144 <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Tree, <span class="keyword">typename</span> Leaf_iterator, <span class="keyword">typename</span> Output_iterator, <span class="keyword">typename</span> Operator&gt;
<a name="l00145"></a>00145 <span class="keywordtype">void</span> reduce_level(
<a name="l00146"></a>00146     <span class="keyword">const</span> Tree              tree,
<a name="l00147"></a>00147     <span class="keyword">const</span> uint32            begin,
<a name="l00148"></a>00148     <span class="keyword">const</span> uint32            end,
<a name="l00149"></a>00149     Leaf_iterator           leaf_values,
<a name="l00150"></a>00150     Output_iterator         out_values,
<a name="l00151"></a>00151     <span class="keyword">const</span> Operator          op)
<a name="l00152"></a>00152 {
<a name="l00153"></a>00153     <span class="keyword">const</span> uint32 n_entries = end - begin;
<a name="l00154"></a>00154 
<a name="l00155"></a>00155     <span class="keyword">const</span> uint32 BLOCK_SIZE = 128;
<a name="l00156"></a>00156     <span class="keyword">const</span> <span class="keywordtype">size_t</span> max_blocks = thrust::detail::backend::cuda::arch::max_active_blocks(reduce_level_kernel&lt;BLOCK_SIZE, Tree, Leaf_iterator, Output_iterator, Operator&gt;, BLOCK_SIZE, 0);
<a name="l00157"></a>00157     <span class="keyword">const</span> <span class="keywordtype">size_t</span> n_blocks   = <a class="code" href="group__vectors.html#ga5809911d15c32de18955c59865379695">nih::min</a>( max_blocks, (n_entries + BLOCK_SIZE-1) / BLOCK_SIZE );
<a name="l00158"></a>00158 
<a name="l00159"></a>00159     reduce_level_kernel&lt;BLOCK_SIZE&gt; &lt;&lt;&lt;n_blocks,BLOCK_SIZE&gt;&gt;&gt; (
<a name="l00160"></a>00160         tree,
<a name="l00161"></a>00161         begin,
<a name="l00162"></a>00162         end,
<a name="l00163"></a>00163         leaf_values,
<a name="l00164"></a>00164         out_values,
<a name="l00165"></a>00165         op );
<a name="l00166"></a>00166 
<a name="l00167"></a>00167     cudaThreadSynchronize();
<a name="l00168"></a>00168 }
<a name="l00169"></a>00169 
<a name="l00170"></a>00170 <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Tree_type&gt;
<a name="l00171"></a><a class="code" href="structnih_1_1cuda_1_1treereduce_1_1reduce.html">00171</a> <span class="keyword">struct </span><a class="code" href="structnih_1_1cuda_1_1treereduce_1_1reduce.html">reduce</a> {};
<a name="l00172"></a>00172 
<a name="l00173"></a>00173 <span class="keyword">template</span> &lt;&gt;
<a name="l00174"></a><a class="code" href="structnih_1_1cuda_1_1treereduce_1_1reduce_3_01breadth__first__tree_01_4.html">00174</a> <span class="keyword">struct </span><a class="code" href="structnih_1_1cuda_1_1treereduce_1_1reduce.html">reduce</a>&lt;<a class="code" href="structnih_1_1breadth__first__tree.html">breadth_first_tree</a>&gt;
<a name="l00175"></a>00175 {
<a name="l00176"></a>00176     <span class="comment">//</span>
<a name="l00177"></a>00177     <span class="comment">// Reduce a bunch of values attached to the leaves of a breadth-first tree.</span>
<a name="l00178"></a>00178     <span class="comment">// The tree is supposed to be laid out in a breadth-first fashion,</span>
<a name="l00179"></a>00179     <span class="comment">// with the beginning of the nodes for level m specified by the map</span>
<a name="l00180"></a>00180     <span class="comment">// levels[m] - where 0 is the root level.</span>
<a name="l00181"></a>00181     <span class="comment">//</span>
<a name="l00182"></a>00182     <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Tree, <span class="keyword">typename</span> Input_iterator, <span class="keyword">typename</span> Output_iterator, <span class="keyword">typename</span> Operator&gt;
<a name="l00183"></a>00183     <span class="keyword">static</span> <span class="keywordtype">void</span> dispatch(
<a name="l00184"></a>00184         <span class="keyword">const</span> Tree              tree,
<a name="l00185"></a>00185         <span class="keyword">const</span> Input_iterator    in_values,
<a name="l00186"></a>00186         Output_iterator         leaf_values,
<a name="l00187"></a>00187         Output_iterator         node_values,
<a name="l00188"></a>00188         <span class="keyword">const</span> Operator          op,
<a name="l00189"></a>00189         <span class="keyword">const</span> <span class="keyword">typename</span> std::iterator_traits&lt;Output_iterator&gt;::value_type def_value)
<a name="l00190"></a>00190     {
<a name="l00191"></a>00191         reduce_leaves(
<a name="l00192"></a>00192             tree,
<a name="l00193"></a>00193             in_values,
<a name="l00194"></a>00194             leaf_values,
<a name="l00195"></a>00195             op,
<a name="l00196"></a>00196             def_value );
<a name="l00197"></a>00197 
<a name="l00198"></a>00198         <span class="keyword">const</span> uint32 n_levels = tree.get_level_count();
<a name="l00199"></a>00199 
<a name="l00200"></a>00200         uint32 offset = 0;
<a name="l00201"></a>00201 
<a name="l00202"></a>00202         <span class="keywordflow">for</span> (int32 level = n_levels-1; level &gt;= 0; --level)
<a name="l00203"></a>00203         {
<a name="l00204"></a>00204             <span class="keyword">const</span> uint32 level_begin = tree.get_level(level);
<a name="l00205"></a>00205             <span class="keyword">const</span> uint32 level_end   = tree.get_level(level+1);
<a name="l00206"></a>00206             <span class="keyword">const</span> uint32 level_size  = level_end - level_begin;
<a name="l00207"></a>00207 
<a name="l00208"></a>00208             <span class="keywordflow">if</span> (level_size == 0)
<a name="l00209"></a>00209                 <span class="keywordflow">continue</span>;
<a name="l00210"></a>00210 
<a name="l00211"></a>00211             reduce_level(
<a name="l00212"></a>00212                 tree,
<a name="l00213"></a>00213                 level_begin,
<a name="l00214"></a>00214                 level_end,
<a name="l00215"></a>00215                 leaf_values,
<a name="l00216"></a>00216                 node_values,
<a name="l00217"></a>00217                 op );
<a name="l00218"></a>00218 
<a name="l00219"></a>00219             offset += level_size;
<a name="l00220"></a>00220         }
<a name="l00221"></a>00221     }
<a name="l00222"></a>00222 
<a name="l00223"></a>00223     <span class="comment">//</span>
<a name="l00224"></a>00224     <span class="comment">// Reduce a bunch of values attached to the leaves of a breadth-first tree.</span>
<a name="l00225"></a>00225     <span class="comment">// The tree is supposed to be laid out in a breadth-first fashion,</span>
<a name="l00226"></a>00226     <span class="comment">// with the beginning of the nodes for level m specified by the map</span>
<a name="l00227"></a>00227     <span class="comment">// levels[m] - where 0 is the root level.</span>
<a name="l00228"></a>00228     <span class="comment">//</span>
<a name="l00229"></a>00229     <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Tree, <span class="keyword">typename</span> Input_iterator, <span class="keyword">typename</span> Output_iterator, <span class="keyword">typename</span> Operator&gt;
<a name="l00230"></a>00230     <span class="keyword">static</span> <span class="keywordtype">void</span> dispatch(
<a name="l00231"></a>00231         <span class="keyword">const</span> Tree              tree,
<a name="l00232"></a>00232         <span class="keyword">const</span> Input_iterator    leaf_values,
<a name="l00233"></a>00233         Output_iterator         node_values,
<a name="l00234"></a>00234         <span class="keyword">const</span> Operator          op)
<a name="l00235"></a>00235     {
<a name="l00236"></a>00236         <span class="keyword">const</span> uint32 n_levels = tree.get_level_count();
<a name="l00237"></a>00237 
<a name="l00238"></a>00238         uint32 offset = 0;
<a name="l00239"></a>00239 
<a name="l00240"></a>00240         <span class="keywordflow">for</span> (int32 level = n_levels-1; level &gt;= 0; --level)
<a name="l00241"></a>00241         {
<a name="l00242"></a>00242             <span class="keyword">const</span> uint32 level_begin = tree.get_level(level);
<a name="l00243"></a>00243             <span class="keyword">const</span> uint32 level_end   = tree.get_level(level+1);
<a name="l00244"></a>00244             <span class="keyword">const</span> uint32 level_size  = level_end - level_begin;
<a name="l00245"></a>00245 
<a name="l00246"></a>00246             <span class="keywordflow">if</span> (level_size == 0)
<a name="l00247"></a>00247                 <span class="keywordflow">continue</span>;
<a name="l00248"></a>00248 
<a name="l00249"></a>00249             reduce_level(
<a name="l00250"></a>00250                 tree,
<a name="l00251"></a>00251                 level_begin,
<a name="l00252"></a>00252                 level_end,
<a name="l00253"></a>00253                 leaf_values,
<a name="l00254"></a>00254                 node_values,
<a name="l00255"></a>00255                 op );
<a name="l00256"></a>00256 
<a name="l00257"></a>00257             offset += level_size;
<a name="l00258"></a>00258         }
<a name="l00259"></a>00259     }
<a name="l00260"></a>00260 };
<a name="l00261"></a>00261 
<a name="l00262"></a>00262 <span class="keyword">template</span> &lt;&gt;
<a name="l00263"></a><a class="code" href="structnih_1_1cuda_1_1treereduce_1_1reduce_3_01depth__first__tree_01_4.html">00263</a> <span class="keyword">struct </span><a class="code" href="structnih_1_1cuda_1_1treereduce_1_1reduce.html">reduce</a>&lt;<a class="code" href="structnih_1_1depth__first__tree.html">depth_first_tree</a>&gt;
<a name="l00264"></a>00264 {
<a name="l00265"></a>00265     <span class="comment">// TODO: implement this!</span>
<a name="l00266"></a>00266 };
<a name="l00267"></a>00267 
<a name="l00268"></a>00268 } <span class="comment">// namespace tree_reduce</span>
<a name="l00269"></a>00269 
<a name="l00270"></a>00270 <span class="comment">//</span>
<a name="l00271"></a>00271 <span class="comment">// Reduce a bunch of values attached to the elemens in the leaves of a tree.</span>
<a name="l00272"></a>00272 <span class="comment">//</span>
<a name="l00273"></a>00273 <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Tree, <span class="keyword">typename</span> Input_iterator, <span class="keyword">typename</span> Output_iterator, <span class="keyword">typename</span> Operator&gt;
<a name="l00274"></a><a class="code" href="group__trees.html#gaa9d77543c5662fa5fc19d34fbcffece1">00274</a> <span class="keywordtype">void</span> <a class="code" href="group__trees.html#gaa9d77543c5662fa5fc19d34fbcffece1">tree_reduce</a>(
<a name="l00275"></a>00275     <span class="keyword">const</span> Tree              tree,
<a name="l00276"></a>00276     <span class="keyword">const</span> Input_iterator    in_values,
<a name="l00277"></a>00277     Output_iterator         leaf_values,
<a name="l00278"></a>00278     Output_iterator         node_values,
<a name="l00279"></a>00279     <span class="keyword">const</span> Operator          op,
<a name="l00280"></a>00280     <span class="keyword">const</span> <span class="keyword">typename</span> std::iterator_traits&lt;Output_iterator&gt;::value_type def_value)
<a name="l00281"></a>00281 {
<a name="l00282"></a>00282     <a class="code" href="structnih_1_1cuda_1_1treereduce_1_1reduce.html">treereduce::reduce&lt;typename Tree::tree_type&gt;::dispatch</a>(
<a name="l00283"></a>00283         tree,
<a name="l00284"></a>00284         in_values,
<a name="l00285"></a>00285         leaf_values,
<a name="l00286"></a>00286         node_values,
<a name="l00287"></a>00287         op,
<a name="l00288"></a>00288         def_value );
<a name="l00289"></a>00289 }
<a name="l00290"></a>00290 
<a name="l00291"></a>00291 <span class="comment">//</span>
<a name="l00292"></a>00292 <span class="comment">// Reduce a bunch of values attached to the leaves of a tree.</span>
<a name="l00293"></a>00293 <span class="comment">//</span>
<a name="l00294"></a>00294 <span class="keyword">template</span> &lt;<span class="keyword">typename</span> Tree, <span class="keyword">typename</span> Input_iterator, <span class="keyword">typename</span> Output_iterator, <span class="keyword">typename</span> Operator&gt;
<a name="l00295"></a><a class="code" href="group__trees.html#ga623ca32c63710202fea743670faeee28">00295</a> <span class="keywordtype">void</span> <a class="code" href="group__trees.html#gaa9d77543c5662fa5fc19d34fbcffece1">tree_reduce</a>(
<a name="l00296"></a>00296     <span class="keyword">const</span> Tree              tree,
<a name="l00297"></a>00297     <span class="keyword">const</span> Input_iterator    in_values,
<a name="l00298"></a>00298     Output_iterator         node_values,
<a name="l00299"></a>00299     <span class="keyword">const</span> Operator          op)
<a name="l00300"></a>00300 {
<a name="l00301"></a>00301     <a class="code" href="structnih_1_1cuda_1_1treereduce_1_1reduce.html">treereduce::reduce&lt;typename Tree::tree_type&gt;::dispatch</a>(
<a name="l00302"></a>00302         tree,
<a name="l00303"></a>00303         in_values,
<a name="l00304"></a>00304         node_values,
<a name="l00305"></a>00305         op );
<a name="l00306"></a>00306 }
<a name="l00307"></a>00307 
<a name="l00308"></a>00308 } <span class="comment">// namespace cuda</span>
<a name="l00309"></a>00309 } <span class="comment">// namespace nih</span>
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